Evidence map›Paper›PMID 30649168›Full record

ArticleAmerican journal of epidemiology2019

Invited Commentary: Improving the Accessibility of Human Microbiome Project Data Through Integration With R/Bioconductor.

Jocelyn C Griffith, Xochitl C Morgan

Abstract readComment
PubMed Publisher
In one paragraph

Article in American journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jocelyn C GriffithDepartment of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
Xochitl C MorganDepartment of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
University of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alterations in the composition of the microbiota have been implicated in many diseases. The Human Microbiome Project (HMP) provides a comprehensive reference data set of the "normal" human microbiome of 242 healthy adults at 5 major body sites. The HMP used both 16S ribosomal RNA gene sequencing and whole-genome metagenomic sequencing to profile the subjects' microbial communities. However, accessing and analyzing the HMP data set still presents technical and bioinformatic challenges, given that researchers must import the microbiome data, integrate phylogenetic trees, and access and merge public and restricted metadata. The HMP16SData R/Bioconductor package developed by Schiffer et al. (Am J Epidemiol. 2019;188(6):1023-1026) greatly simplifies access to the HMP data by combining 16S taxonomic abundance data, public patient metadata, and phylogenetic trees as a single data object. The authors also provide an interface for users with approved Database of Genotypes and Phenotypes (dbGaP) projects to easily retrieve and merge the controlled-access HMP metadata. This package has a broad range of appeal to researchers across disciplines and with various levels of expertise in using R and/or other statistical tools, which translates to improved data accessibility for public health research, with data from healthy individuals serving as a reference for disease-associated studies.

Indexed as

MicrobiotaComputational BiologyHumansMetagenomePhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16SBioconductordatabasesHuman Microbiome ProjectmicrobiomeR

Identifiers

PMID30649168
OpenAlexW2910665281

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.